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//
// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <OpaqueDelegateUtils.hpp>
namespace armnnOpaqueDelegate
{
TfLiteStatus VisitGatherOperator(DelegateData& delegateData,
TfLiteOpaqueContext* tfLiteContext,
TfLiteOpaqueNode* tfLiteNode,
int nodeIndex,
int32_t operatorCode)
{
TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
int numInputs = 0;
const int* inputTensors;
if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ",
nodeIndex);
return kTfLiteError;
}
int numOutputs = 0;
const int* outputTensors;
if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ",
nodeIndex);
return kTfLiteError;
}
const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext,
inputTensors[0]);
if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
{
return kTfLiteError;
}
const TfLiteOpaqueTensor* tfLiteIndicesTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext,
inputTensors[1]);
if (!IsValid(tfLiteContext, tfLiteIndicesTensor, operatorCode, nodeIndex))
{
return kTfLiteError;
}
const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext,
outputTensors[0]);
if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
{
return kTfLiteError;
}
auto* tfLiteNodeParameters = reinterpret_cast<TfLiteGatherParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
auto axis = tfLiteNodeParameters->axis;
const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
const armnn::TensorInfo& indicesTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteIndicesTensor);
const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
armnn::GatherDescriptor gatherDescriptor;
gatherDescriptor.m_Axis = axis;
auto inputDimensions = static_cast<int32_t>(inputTensorInfo.GetNumDimensions());
auto indicesDimensions = indicesTensorInfo.GetNumDimensions();
auto outputDimensions = outputTensorInfo.GetNumDimensions();
if (((axis < -inputDimensions) && (axis < 0)) || ((axis >= inputDimensions) && (axis > 0)))
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnOpaqueDelegate: Operation has invalid axis: %d. It is out of bounds [-%d, %d))",
axis, inputDimensions, inputDimensions);
return kTfLiteError;
}
if (outputDimensions != static_cast<unsigned int>(inputDimensions) + indicesDimensions - 1)
{
TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
tfLiteContext,
"TfLiteArmnnOpaqueDelegate: Operation has invalid output dimensions: %d. "
"Output must be an (%d + %d - 1)-D tensor",
outputDimensions, inputDimensions, indicesDimensions);
return kTfLiteError;
}
armnn::BackendId setBackend;
if (!delegateData.m_Network)
{
// Check if supported
bool isSupported = false;
FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("GATHER",
tfLiteContext,
IsGatherSupported,
delegateData.m_Backends,
isSupported,
setBackend,
inputTensorInfo,
indicesTensorInfo,
outputTensorInfo,
gatherDescriptor);
return isSupported ? kTfLiteOk : kTfLiteError;
}
auto layerName = GetName(armnn::LayerType::Gather, nodeIndex);
armnn::IConnectableLayer* layer = delegateData.m_Network->AddGatherLayer(gatherDescriptor, layerName.c_str());
layer->SetBackendId(setBackend);
ARMNN_ASSERT(layer != nullptr);
layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
auto inputsTensorsProcess = ProcessInputs(layer,
delegateData,
tfLiteContext,
tfLiteNode,
nodeIndex);
if (inputsTensorsProcess == kTfLiteError)
{
return inputsTensorsProcess;
}
return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
}
} // namespace armnnOpaqueDelegate
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